Project Summary/Abstract Many outcome predictors used in precision medicine are based upon experience with populations of previous patients who are similar in important ways. However, standard Electronic Health Record systems (EHRs) seldom support real-time population queries and therefore cannot administer precision medicine as part of their integrated decision support for clinicians. Furthermore, the data upon which many precision medicine algorithms operate is not available in standard EMRs because it comes from advanced genomics, imaging analytics, and other data modalities which fall outside of the data domains of standard EHR platforms. We propose developing Informatics for Integrating Biology and the Bedside (i2b2), a well- established, open source, integrated, big data analytic platform that is currently used at over 140 hospitals and medical centers, to study phenotype/genotype comparisons and incorporate it into the EHR using small, connected applications named Substitutable Medical Applications and Reusable Technologies (SMART). We will take the Partners HealthCare genomics platform, GeneInsight, and integrate its data into our Epic EHR workflow using i2b2. We will then test specific decision support algorithms for inherited cardiac diseases. The resulting software will be open source and allow integration of genomics-based, big data decision support algorithms broadly into EHRs. We will also use these same data to provide decision support to laboratory professionals who classify variants relative to their clinical effects. Standard methods of representing these data will be used to make the algorithms transportable and universally applicable. The Decision Support Apps that are created will be evaluated not only for their potential impact upon clinical care, but also for their durability and adaptability to different healthcare environments.